code: def get_integer_seed(seed):
      """Returns an integer seed in [0, 2**31).
  
      Args:
        seed: A seed suitable to be passed to `sanitize_seed`.
  
      Returns:
        integer_seed: A Python integer (if seed was a Python integer or we're in
        JAX) or an integer Tensor.
      """
      if isinstance(seed, six.integer_types):
          return seed % (2**31)
      seed = sanitize_seed(seed)
      integer_seed = tf.random.stateless_uniform(
          shape=[], seed=seed, minval=0, maxval=2**31, dtype=tf.int32
      )
      if JAX_MODE:
          # This function isn't ever used in a jit context, so we can eagerly convert
          # it to an integer to simplify caller's code.
          integer_seed = int(integer_seed)
      return integer_seed
  
file_path: probability/tensorflow_probability/python/internal/samplers.py
imports: import hashlib
  import warnings
  import numpy
  import six
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import prefer_static
label_desc: Use image node_id 4 for calling a global function with example usage: get_integer_seed(seed) and returns: integer_seed, unknown